For over 30 years, quests for rare genetic variants causing disease were rewarded for having good positional sense (linkage analysis) and educated guesswork (candidate gene analysis). Recently, novel 'NextGen' DNA sequencing methods have found rare variants by sequencing all known exons (the 'exome'). This application of a genomics solution to a traditionally genetics problem has fundamentally redefined how to solve the 'rare variant' question. The paradigm shift may soon render traditional PCR based analyses obsolete and is reminiscent of how GWAS studies (e.g. NIH GWAS Initiative) are solving the common variant problem. However, currently exome sequencing has mainly explored rare diseases, false positives remain an issue, and validation of findings in large follow-up cohorts has not been done. Our group has been studying a decidedly morbid condition and 'non-rare' condition, hereditary dilated cardiomyopathy (DCM) (prevalence ~1:500), which represents the first and third leading causes of heart transplant and heart failure, respectively. Over 600 families with extensive clinical data and DNA have been collected by our international registry. A key existing knowledge gap is that two-thirds of the genetic causes of DCM are still unknown. Traditional approaches (linkage/candidate analyses) have largely stalled, confounded in part by high genetic heterogeneity and the difficulties of locating large enough families for study. Novel approaches are needed to address bridge this knowledge gap, improve our understanding of disease etiology, and direct us to new targets for DCM treatment. To solve this knowledge gap, we propose to use NextGen whole genome sequencing large, multigenerational families. Our hypothesis is that our two-step genomics solution of 'gene discovery' followed by 'gene validation' will reveal novel DCM genes. In Aim 1, 20 large families will undergo genome sequencing for gene discovery (Illumina HiSeq2000). Three innovative bioinformatic steps (filtering by segregation / by gene/pathway analysis / a novel bioinformatic analysis that prioritizes exome variants) will markedly reducing false-positive findings. In Aim 2, novel genes (Aim 1) will be sequenced in a validation cohort of 200 DCM families. Innovative components of our project are: genome sequencing in a 'non-rare' and highly morbid disease, use of segregation analysis in extended pedigrees, our novel bioinformatic strategy we call E1P2I3, and validation in a replication cohort. The impact of this work will include discovery of novel DCM genes, development of new DCM genetic tests, improvement in understanding of DCM etiology, and illumination of potential new therapeutic strategies.